simonorozcoarias / ML_DL_microArraysLinks
Here, we describe the comparison of the most used algorithms in classical ML and DL to classify carcinogenic tumors described on 11_tumor data base, obtaining accuracies between 76.97% and 100% for tumor identification. Our results bring up a more efficient an accurate classification method based on gene expression (microarray data) and ML/DL al…
☆11Updated 5 years ago
Alternatives and similar repositories for ML_DL_microArrays
Users that are interested in ML_DL_microArrays are comparing it to the libraries listed below
Sorting:
- DCAP:Integrating multi-omics data with deep learning for predicting cancer prognosis☆21Updated 4 years ago
- This is the repository for paper titled as "Convolutional neural network models for cancer type prediction based on gene expression".☆52Updated 6 years ago
- This repository contains code used to build and interpret a deep learning model. It is a DNN classifier trained using gene expression dat…☆9Updated 4 years ago
- Deep-Learning framework for multi-omic and survival data integration☆82Updated last year
- Clinical data for the TCGA PanCancer Atlas☆15Updated 5 years ago
- Fusion strategies to build multimodal predictors for the prediction of immunotherapy response in non-small cell lung cancer☆11Updated 5 months ago
- OncoNetExplainer: Explainable Prediction of Cancer Types Based on Gene Expression Data☆11Updated 2 years ago
- ☆14Updated last year
- ☆55Updated 2 years ago
- ☆33Updated 3 years ago
- Classifying tumor types based on Whole Genome Sequencing (WGS) data☆48Updated last year
- SALMON: Survival Analysis Learning with Multi-Omics Neural Networks☆67Updated 8 months ago
- Pathway-based sparse deep neural network for survival analysis☆38Updated last year
- ☆47Updated 8 years ago
- jupyter notebook; perform differential gene expression analysis using DESeq2 on TCGA RNAseq data☆32Updated 6 years ago
- Code for paper "A deep profile of gene expression across 18 human cancers"☆25Updated 6 months ago
- SEQUOIA: Digital profiling of cancer transcriptomes with grouped vision attention☆41Updated 3 weeks ago
- Multi-task deep learning framework for multi-omics data analysis☆45Updated 3 years ago
- ☆34Updated 3 years ago
- ☆19Updated 4 years ago
- This project consists of three parts: Random forest model for GC diagnosis and Predict the survival outcomes of GC patient using RSF meth…☆28Updated 7 months ago
- Python module for genetic analyses☆14Updated 2 months ago
- DeepSpot: Leveraging Spatial Context for Enhanced Spatial Transcriptomics Prediction from H&E Images☆49Updated 2 weeks ago
- Implementation of DeepSurv using Keras☆52Updated last year
- Reproducing the experiments of the DestVI paper☆18Updated 3 years ago
- A pan-cancer platform for mutation prediction from routine histology☆68Updated 4 years ago
- Multimodality Fusion Subtyping (Nature Communications)☆21Updated 2 months ago
- Deep learning reveals predictive sequence concepts within immune repertoires to immunotherapy☆15Updated 2 years ago
- Self-supervised representation learning combining GTEx histology, RNA-seq and WGS☆29Updated 2 months ago
- Python API for Xena Hub☆53Updated 2 years ago